Biological aerosol detectors are used to detect the presence of biological molecules in aerosol samples. The detectors are typically placed in locations where the potential for a chemical attack or industrial accident exists. Prior to placing the detectors in the field, it is desirable to test and characterize their responsiveness to expected signal events under operating conditions, including the responsiveness of any software that is used to operate the detector.
Under operating conditions, biological aerosol detectors can be expected to continuously collect data for long periods of time, such as weeks, months or years. The data is expected to consist largely of background signals and events and to reflect the absence of signal events that indicate the presence of biological molecules. To be effective under such operating conditions, biological aerosol detectors must be able to accurately and efficiently detect biological molecules in an aerosol sample even when the molecules are only present for a relatively short periods of time within much longer observation periods.
Biological aerosol detectors typically detect the presence of biological molecules using some form of peak detection algorithm. Peak detection algorithms, as their names imply, detect peaks in a data stream that rise above a background signal level, and that are indicative of signal events. To test the accuracy and efficiency of peak detection algorithms, the algorithms must be run on large samples of realistic looking data. Often, it is impractical to spend the weeks, months, or even years needed to collecting the amount of data that is needed to optimize and accurately test peak detection algorithms. Consequently, a method is needed for generating a synthetic signal that in a short period of time, accurately reflects the characteristics of the actual data signal the biological aerosol detector is expected to collect over a longer time period.